This application relates to managing content choices, for example, such as in an electronic programming guide used in a television (TV) environment.
A computer system 100 illustrated in FIG. 1 represents a typical hardware setup for executing software that allows a user to perform tasks such as communicating with other computer users, accessing various computer resources, and viewing, creating, or otherwise manipulating electronic contentxe2x80x94that is, any combination of text, images, movies, music or other sounds, animations, 3D virtual worlds, and links to other objects. The system includes various input/output (I/O) devices (mouse 102, keyboard 104, display 106) and a general purpose computer 108 having a central processor unit (CPU) 110, an I/O unit 112 and a memory 114 that stores data and various programs such as an operating system 116, and one or more application programs 118.
The computer system 100 also typically includes some sort of communications card or device 120 (for example, a modem or network adapter) for exchanging data with a network 122 via a communications link 124 (for example, a telephone line). A content provider provides access to network content in addition to various services associated with the content. Examples of content providers include Internet service providers (ISPs) 126 such as ATandT WorldNet and UUNet or online service providers (OSPs) 128 such as America Online and Compuserve.
As shown in FIG. 2, a user of the computer system 100 can access electronic content or other resources either stored locally at the user""s own client system 202 (for example, a personal or laptop computer) or remotely at one or more server systems 200. An example of a server system is a host computer that provides subscribers with online computer services such as e-mail, e-commerce, chat rooms, Internet access, electronic newspapers and magazines, etc. Users of a host computer""s online services typically communicate with one or more central server systems 200 through client software executing on their respective client systems 202.
In practice, a server system 200 typically will not be a single monolithic entity but rather will be a network of interconnected server computers, possibly physically dispersed from each other, each dedicated to its own set of duties and/or to a particular geographical region. In such a case, the individual servers are interconnected by a network of communication links, in known fashion. One such server system is xe2x80x9cAmerica Online 4.0xe2x80x9d from America Online, Incorporated of Virginia.
A xe2x80x9cbrowserxe2x80x9d is an example of client software that enables users to access and view electronic content stored either locally or remotely, such as in a network environment (local area network (LAN), intranet, Internet). A browser typically is used for displaying documents described in Hyper-Text Markup Language (HTML) and stored on servers connected to a network such as the Internet.
A user instructs a browser to access an HTML document, or web page, by specifying a network addressxe2x80x94or Uniform Resource Locator (URL)xe2x80x94at which a desired document resides. In response, the browser contacts the corresponding server hosting the requested web page, retrieves the one or more files that make up the web page, and then displays the web page in a window on the user""s computer screen.
FIG. 3 is a screen shot of a browser application 300 (Internet Explorer) displaying a typical HTML document, or web page 302. As shown therein, a single web page may be composed of several different files potentially of different data types 304 (for example, text, images, virtual worlds, sounds, or movies). In addition, a web page can include links 306, or pointers, to other resources (for example, web pages or individual files) available on the network. Each link has an associated URL pointing to a location on the network. When a user clicks on, or otherwise selects a displayed link, the browser automatically will retrieve the web page or other resource corresponding to the link""s associated URL and display it to, or execute if for, the user.
Referring to FIG. 4, a xe2x80x9cweb-based TVxe2x80x9d system 400 has been developed that makes dual usage of TV sets 402. That is, a user of web-based TV either can watch TV or view web pages and otherwise xe2x80x9csurfxe2x80x9d the Internet. In this regard, a special purpose computer 404, referred to as a xe2x80x9cset top device,xe2x80x9d has been developed and used in connection with standard TV sets 402 for viewing web pages on the Internet. The set top device 404 essentially has the same basic components as the general purpose computer 108 illustrated in FIG. 1 (including, for example, CPU 110 and memory 114), except that it also includes a TV tuner 406 for receiving broadcast and/or cable TV signals 407. The set top device 404 thus can selectively display two different sources of content (TV programming received by TV tuner 406 and web or network content received by communications device 120) on the TV monitor 402 connected to the set top device 404.
Accessories may be added to the web-based TV system 400, for example, a wireless keyboard 408 similar to keyboard 104 but with specialized keys that are designed for use in the web-based TV system 400 to make Internet access and surfing easier. Additionally, a wireless remote control 410 may be used to control the set top device 404 and to facilitate channel surfing and web-based TV connections via various buttons 412 that may be specialized for the web-based TV system 400.
An example of an existing web-based TV system 400 is WebTV by Microsoft. Information about the WebTV product may be found at WebTV""s web page at www.webtv.net under the Products section at www.webtv.net/products.
Typically, to facilitate viewing selection, TV systems, both web-based and conventional, may employ an electronic programming guide (EPG) 500 such as the one shown in FIG. 5. The EPG 500 usually is displayed on a dedicated channel and occupies the majority of the TV screen 504. Once a user selects a date 506 and day of the week 508, the user may scroll (shown as arrows 510) through channels 502 and time slots 512 to see what viewing choices are available. A status bar 514 may be displayed on the EPG 500 that gives current TV settings and time. The EPG 500 may display either a traditional TV channel (such as CNN) in a miniature viewing area 516 or a special TV channel (such as PAY-PER-VIEW previews) associated with the EPG 500.
Due to an increase in available bandwidth in communications signals such as telephone and cable lines, the number of content choices available to a user or subscriber of a web-based TV system 400 has grown dramatically in recent years. Accordingly, the present inventors recognized that it would be desirable to provide users with an intelligent mechanism for managing and presenting their available content choices. The present inventors also recognized that an intelligent mechanism would account for a user""s limited investment time and a TV screen""s limited space or xe2x80x9creal estate.xe2x80x9d
Various implementations may include one or more of the following features.
In one general aspect, a computer-implemented method manages a user""s content choices. The method includes predicting one or more content choices that are likely to be of interest to a user based on a degree of matching between a psychographic profile for the user and available content. The predicted content choices are then presented to the user.
Embodiments may include one or more of the following features.
The method may include receiving an identifier from a content provider, the identifier indicating the psychographic profile for the user. The method may further include searching a profile database to determine the psychographic profile indicated by the identifier.
The method may also include monitoring user activities to continually refine the user""s psychographic profile. Monitoring may include monitoring one or more of a user""s inputs, the inputs including keystrokes, mouse clicks, remote control button activations, or any combination thereof. Monitoring may also include detecting patterns in the user""s inputs, and encoding and storing the detected patterns in an archive of the user""s inputs.
User activities may include a user""s visit to a content choice, a user""s purchase of a product, or a user""s history of content selections. Alternatively, user activities may include a user""s response to one or more questions or prompts.
The psychographic profile may be based on a user""s behavior. Furthermore, the user""s behavior may include browsing and purchasing patterns. Alternatively, the psychographic profile may be based on other users"" behavior. Other users"" behavior may include demographic or affinity patterns of users.
The degree of matching may be based on external conditions. Additionally, the external conditions may include weather conditions, temporal conditions or user location conditions. Likewise, the degree of matching may be based on expert choices. The degree of matching may be based on premium content provider choices. And lastly, the degree of matching may be based on ranked lists of content choices.
Predicting one or more content choices may include randomly selecting one or more content choices.
The matching may be based on probability-weighted mappings from a psychographic profile to one or more categories of content. A content category may include a variety of experiences, resources, and capabilities of content choices that fall within one or more of the content categories. Furthermore, content categorization may include accessing and classifying a substantial plurality of content choices.
Content categorization may include analyzing data within content to determine relationships among content data. Data relationships may include relevancy that indicates whether the data is what the user is searching for. Data relationships also may include parallax that indicates a different view of the same data exists. A registry data relationship may be included which indicates an object with which the data is affiliated. Data relationships may include selection that indicates how the data was collected. A criticism data relationship may be included, the criticism relationship indicating if another piece of data exists that is critical of the current data. Data relationships may further include construction that indicates a structure of the data. Moreover, data relationships may include position that indicates a realtime position and direction of the user.
Content categorization may include associating one or more users"" actions with other users"" actions.
The content managing method may also include determining a user""s psychographic profile by determining a configuration of a user""s computer system.
Presenting the predicted content choices may include outputting the content choices to a content provider. Outputting the content choices to the content provider may include causing the content provider to display content choices in a navigatable electronic programming guide.
In another general aspect, a computer-implemented method of managing a user""s content choices includes receiving data descriptive of a user""s patterns. A psychographic profile is built for the user based on the received pattern data. The method also includes receiving data relating to content choices. Content categories associated with the received content choices are determined. Furthermore, the user""s psychographic profile is predictively mapped to the determined content categories. Based on the predictive mapping, the method selectively provides content choices to the user.
Embodiments may include one or more of the following. The environment may include a special purpose computer.
A user""s patterns may include viewing patterns, or purchasing patterns. The user""s patterns may be based on a user""s answers to questions, or a user""s previous behavior.
The psychographic profile may be based on external events. Likewise, the psychographic profile may be based on content choices of one or more users in a region, content choices of one or more users during an interval of time, or content choices of one or more users relative to weather pattens.
The content managing method may also include assigning an alpha-numeric identifier to a psychographic profile. Content categories may include one or more content choices that exhibit similar attributes. A content choice may be associated with one or more content categories.
In another general aspect, a content choice prediction architecture includes a psychographic profile defining a user""s content preferences, and two or more content categories. The architecture also includes a content manager for predicting content choices likely to be of interest to the user based on a degree of matching between the user""s psychographic profile and one or more of the content categories.
Embodiments may include one or more of the following. The user""s content preferences may include patterns of content viewing and purchasing.
Each content category may include one or more content choices that are distinguished from other content choices. The distinguishing may be based on resource available at and capabilities of the content choices.
The content manager may include a human that determines the degree of matching between the user""s psychographic profile and one or more content categories. The human may populate and maintain a meta-rules database, associated with the content manager, with meta-rules that instruct the content manager how to monitor changing content and psychographic profiles to determine degrees of matching between a psychographic profile and one or more content choices.
The content manager may include a processor that automatically determines the degree of matching between the user""s psychographic profile and one or more content categories. The content manager may include a neural network that continually adjusts its prediction based on changes in psychographic profiles, content choices, and relationships between content choices.
In another general aspect, a computer-implemented method of installing content choice prediction architecture includes manually building a predictive content system. The manual building includes evaluating raw patterns for users, and determining new psychographic profiles based on the raw pattern evaluation. The manual building further includes browsing content choices to select content attributes, and categorizing content choices based on the browsing. The manual building also include mapping psychographic profiles with content categories, and codifying the mapping in a map database. The architecture-installing method includes developing the predictive content system into a self-teaching system that relies on a predictive content manager that automatically predicts one or more content choices that are likely to be of interest to a user based on the mapping.
Embodiments may include one or more of the following. Determining new psychographic profiles may include determining whether the raw user patterns constitute new patterns for that user, and if so, storing a new psychographic profile identifier in an identifier database.
Determining new psychographic profiles may include determining whether the raw user patterns qualify as new patterns, and if so, updating an existing or storing a new psychographic profile in a profile database.
Developing may include populating a meta-rules database, associated with the predictive content system, with meta-rules that dictate to the predictive content system how to scan through content choices and raw user patterns to amend the codified mapping.
The architecture-installing method may also include updating an existing or storing a new content category based on the browsing.
The systems and techniques described here may provide one or more of the following advantages.
An intelligent content managing system provides users with a mechanism for managing and presenting their available content choices. In a broadband environment that uses, for example, Digital Subscriber Line (DSL) technology, the intelligent content managing system is especially useful. When applied to a web-based TV environment, such an intelligent content manager provides viewers with content choices (for example, TV channels, web pages, etc.) that are likely to be of interest, while minimizing the amount of time and effort spent by the users in locating desirable content. Moreover, the content choices provided to each viewer are specifically tailored to that user""s likes and dislikes. Because the user plays a relatively passive role in the content management, the user is able to spend less time searching for desirable content and more time enjoying the provided content choices.